Examples of 'asymptotic normality' in a sentence
Meaning of "asymptotic normality"
asymptotic normality - a statistical concept that describes the behavior of a sequence of random variables as the sample size increases. In simple terms, it means that as the sample size becomes larger and larger, the distribution of the sample mean approaches a normal distribution
How to use "asymptotic normality" in a sentence
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asymptotic normality
We show the asymptotic normality of the estimators.
Two key convergence properties are consistency and asymptotic normality.
Consistency and asymptotic normality of the estimators are proven.
It will also be veri ed the consistency and the asymptotic normality of the estimators.
Consistency and asymptotic normality of the estimator are established.
The consistency of the estimator and its asymptotic normality are established.
Consistency and asymptotic normality of the estimates are established.
We first show the pointwise weak and strong consistencies as wellas the asymptotic normality.
The consistency and the asymptotic normality of estimators are proved.
Asymptotic normality of the quasi maximum likelihood estimator for multidimensional causal processes.
We prove consistency and asymptotic normality for this estimator.
The asymptotic normality of the first estimators is logically obtained from the second ones.
We establish the pointwise consistency and asymptotic normality of our estimators.
Their asymptotic normality is established.
Then we find the modified conditions for the asymptotic normality of these estimators.
See also
The consistency and asymptotic normality behaviors are also investigated for the estimators.
Sufficient conditions for this convergence and for the asymptotic normality of the estimator are found.
Consistency and asymptotic normality are proved for these estimators.
We study its asymptotic performance, and we prove its asymptotic normality.
We establish there the asymptotic normality of the normalized stopping rule.
Then, we demonstrate the consistency of this estimator, and let us establish its asymptotic normality.
We derive strong consistency and asymptotic normality for all our estimates.
We prove that the estimates obtained from such procedures satisfy consistency, sparsity, and asymptotic normality.
We establish the consistency and the asymptotic normality of the maximum likelihood estimator.
The asymptotic normality of this statistical processes was only given for tau > 1/2.
In a first chapter, we establish the asymptotic normality of these estimators.
We prove its asymptotic normality and give the explicit expression of the variance term.
Then, we establish the consistency and asymptotic normality of the estimator offers.
This test is based on LeCam 's theory of local asymptotic normality ( LAN ).
The notion of local asymptotic normality was introduced by Le Cam 1960.
In a second time, we study the asymptotic normality of those estimators.
At the end of the thesis, we prove asymptotic normality for the fluctuations.
Hypothesis testing is performed by using the asymptotic normality of the maximum-likelihood estimators.
To start with, we review the consistency and asymptotic normality properties of the CGMM estimator.
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